The efficacy of traditional acupuncture on patients with chronic neck pain: study protocol of a randomized controlled trial
Bibliographic record
Abstract
BACKGROUND: A large number of randomized trials on the use of acupuncture to treat chronic pain have been conducted. However, there is considerable controversy regarding the effectiveness of acupuncture. We designed a randomized trial involving patients with chronic neck pain (CNP) to investigate whether acupuncture is more effective than a placebo in treating CNP. METHODS/DESIGN: A five-arm, parallel, single-blinded, randomized, sham-controlled trial was designed. Patients with CNP of more than 3 months' duration are being recruited from Guangdong Provincial Hospital of Chinese Medicine (China). Following examination, 175 patients will be randomized into one of five groups (35 patients in each group) as follows: a traditional acupuncture group (group A), a shallow-puncture group (group B), a non-acupoint acupuncture group (group C), a non-acupoint shallow-puncture group (group D) and a sham-puncture group (group E). The interventions will last for 20 min and will be carried out twice a week for 5 weeks. The primary outcome will be evaluated by changes in the Northwick Park Neck Pain Questionnaire (NPQ). Secondary outcomes will be measured by the pain threshold, the Short Form McGill Pain Questionnaire-2 (SF-MPQ-2), the 36-Item Short-Form Health Survey (SF-36) and diary entries. Analysis of the data will be performed at baseline, at the end of the intervention and at 3 months' follow-up. The safety of acupuncture will be evaluated at each treatment period. DISCUSSION: The purpose of this trial is to determine whether traditional acupuncture is more effective for chronic pain relief than sham acupuncture in adults with CNP, and to determine which type of sham acupuncture is the optimal control for clinical trials. TRIAL REGISTRATION: Chinese Clinical Trial Registry: ChiCTR-IOR-15006886 . Registered on 2 July 2015.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.048 | 0.044 |
| Meta-epidemiology (narrow) | 0.008 | 0.004 |
| Meta-epidemiology (broad) | 0.016 | 0.007 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.009 | 0.008 |
| Insufficient payload (model declined to judge) | 0.052 | 0.008 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".